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Found 18 papers, 2 papers with code
Fact-checking based fake news detection: a review
This paper reviews and summarizes the research results on fact-based fake news from the perspectives of tasks and problems, algorithm strategies, and datasets.
From Covert Hiding to Visual Editing: Robust Generative Video Steganography
Traditional video steganography methods are based on modifying the covert space for embedding, whereas we propose an innovative approach that embeds secret message within semantic feature for steganography during the video editing process.
PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuning
We observe that humans tend to discern the authenticity of an image based on both semantic and high-frequency information, inspired by which, the proposed framework leverages rich semantic knowledge from pre-trained visual foundation models to assist IML.
DRAW: Defending Camera-shooted RAW against Image Manipulation
RAW files are the initial measurement of scene radiance widely used in most cameras, and the ubiquitously-used RGB images are converted from RAW data through Image Signal Processing (ISP) pipelines.
RetouchingFFHQ: A Large-scale Dataset for Fine-grained Face Retouching Detection
However, the lack of large-scale and fine-grained face retouching datasets has been a major obstacle to progress in this field.
StyleStegan: Leak-free Style Transfer Based on Feature Steganography
Our method consists of two main components: a style transfer method that accomplishes artistic stylization on the original image and an image steganography method that embeds content feature secrets on the stylized image.
Multi-modal Fake News Detection on Social Media via Multi-grained Information Fusion
The easy sharing of multimedia content on social media has caused a rapid dissemination of fake news, which threatens society's stability and security.
Learning to Immunize Images for Tamper Localization and Self-Recovery
Image immunization (Imuge) is a technology of protecting the images by introducing trivial perturbation, so that the protected images are immune to the viruses in that the tampered contents can be auto-recovered.
Image Generation Network for Covert Transmission in Online Social Network
Online social networks have stimulated communications over the Internet more than ever, making it possible for secret message transmission over such noisy channels.
Robust Watermarking for Video Forgery Detection with Improved Imperceptibility and Robustness
We jointly train a 3D-UNet-based watermark embedding network and a decoder that predicts the tampering mask.
Bootstrapping Multi-view Representations for Fake News Detection
Representations from each view are separately used to coarsely predict the fidelity of the whole news, and the multimodal representations are able to predict the cross-modal consistency.
Image Protection for Robust Cropping Localization and Recovery
Existing image cropping detection schemes ignore that recovering the cropped-out contents can unveil the purpose of the behaved cropping attack.
A DTCWT-SVD Based Video Watermarking resistant to frame rate conversion
To address this issue, we present a new video watermarking based on joint Dual-Tree Cosine Wavelet Transformation (DTCWT) and Singular Value Decomposition (SVD), which is resistant to frame rate conversion.
Multimodal Fake News Detection via CLIP-Guided Learning
The results indicate that the proposed framework has a better capability in mining crucial features for fake news detection.
Invertible Image Dataset Protection
We develop a reversible adversarial example generator (RAEG) that introduces slight changes to the images to fool traditional classification models.
From Image to Imuge: Immunized Image Generation
At the recipient's side, the verifying network localizes the malicious modifications, and the original content can be approximately recovered by the decoder, despite the presence of the attacks.
Hiding Images into Images with Real-world Robustness
The existing image embedding networks are basically vulnerable to malicious attacks such as JPEG compression and noise adding, not applicable for real-world copyright protection tasks.
RWN: Robust Watermarking Network for Image Cropping Localization
At the recipient's side, ACP extracts the watermark from the attacked image, and we conduct feature matching on the original and extracted watermark to locate the position of the crop in the original image plane.
